A method and system for treating aquaculture tailwater using rice straw modified biochar

Abstract

The present invention belongs to the field of data processing technology, and proposes a method and system for treating aquaculture tailwater using rice straw modified biochar, which is specifically as follows: firstly, a flow sensor is arranged at the water inlet of a fluidized bed to read the water inlet flow, and the aeration rate is obtained in real time from the aeration device of the fluidized bed, and then when the change rate of the water inlet flow exceeds a threshold, an adaptive aeration rate adjustment intervention is performed; wherein the process of adaptive aeration rate adjustment intervention includes: constructing an aeration adaptation model through the water inlet flow and the aeration rate to obtain an adaptation pairing amount; and controlling the aeration rate according to the adaptation pairing amount. The method dynamically quantifies the risk of fluidized medium particles collapsing due to changes in the water inlet flow and the transition of the aeration rate when the fluidized medium particles constructed using rice straw modified biochar are used for aquaculture tailwater treatment, so as to prevent the fluidized medium particles constructed using rice straw modified biochar from being crushed due to excessive aeration or a surge in water flow, thereby improving the operation quality and service life of the fluidized bed.

Description

Technical Field

[0001] The invention belongs to the technical field of data processing and automatic regulation, and particularly relates to a method and system for treating aquaculture tail water using rice straw-modified biochar. Background Art

[0002] The application of biochar in aquaculture tailwater treatment is a promising and environmentally friendly research direction, especially in the field of freshwater aquaculture. Aquaculture tailwater usually contains high concentrations of nitrogen, phosphorus or organic pollutants. If it is discharged directly without treatment, it will cause serious pollution to the water environment. Biochar provides an effective solution to this problem with its unique physical and chemical properties, including the adsorption of biochar, as a microbial carrier or the optimization of pH and redox conditions. Among them, the modified biochar with rice straw as raw material is abundant and low-cost. Compared with the traditional modified biochar with wood as raw material, straw biochar has stronger adsorption capacity. This is because it naturally contains a high silica component, which can enhance its mechanical strength and make the adsorption pores not easy to collapse or deform and lose adsorption. At the same time, alkaline minerals such as potassium, calcium, and magnesium in rice straw effectively promote the adsorption and fixation of phosphate to achieve the effect of phosphorus removal in aquaculture tailwater, which is suitable for promotion in aquaculture tailwater treatment scenarios based on fluidized beds. In the process of aquaculture tailwater treatment using fluidized bed technology, the fluidized medium particles prepared by adding straw biochar can not only carry decontamination bacteria such as nitrifying bacteria or phosphate-dissolving bacteria, but also efficiently absorb metals or nitrogen and phosphorus substances in the water. However, the fluidized medium particles are prone to collapse during the application process, resulting in pipeline blockage, reduced tailwater treatment efficiency, and loss of fluidized medium particles in the fluidized bed, which gradually collapses the fluidized bed tailwater treatment system, especially water treatment efficiency, which is an advantage of fluidized bed tailwater treatment compared with other tailwater treatments such as fixed bed reactors. The problem of gradual collapse of the fluidized bed tailwater treatment system is due to the fact that an aeration device is required in the fluidized bed to drive the fluidized medium particles to suspend and form a dynamic state similar to a fluid, increase the contact area between water and the medium to promote the removal efficiency of pollutants in the water, and the fluidized medium particles prepared by adding straw biochar are rich in rice straw modified biochar, which has a high mechanical strength, so that its structure is relatively brittle and fragile, so that when the aeration rate exceeds the required flow rate, the water flow or air flow that occurs is too strong to crush the fluidized particle medium in the fluidized bed. Therefore, there is an urgent need for a dynamic control method for aeration in the process of aquaculture tailwater treatment using fluidized medium particles prepared by adding straw biochar. Summary of the invention

[0003] The purpose of the present invention is to propose a method and system for treating aquaculture tailwater using rice straw-modified biochar, so as to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0004] In order to achieve the above object, according to one aspect of the present invention, a method for treating aquaculture tailwater using rice straw modified biochar is provided, the method comprising the following steps:

[0005] S100, arranging a flow sensor at the water inlet of the fluidized bed to read the water inlet flow;

[0006] S200, obtaining the aeration rate from the aeration device of the fluidized bed in real time;

[0007] S300, when the rate of change of the water inlet flow exceeds a threshold, an adaptive aeration rate adjustment intervention is performed;

[0008] The process of adaptive aeration rate regulation intervention includes: S301, constructing an aeration adaptation model through water inlet flow and aeration rate to obtain an adaptation pairing amount; S302, controlling the aeration rate according to the adaptation pairing amount.

[0009] Further, in step S100, a flow sensor is arranged at the water inlet of the fluidized bed, and the method for reading the water inlet flow is: the flow sensor selects any one of an electromagnetic flowmeter, an ultrasonic flowmeter or an ultrasonic flowmeter, and the flow sensor is arranged in a straight pipe position more than 10 times the pipe diameter away from the flow valve in the pipeline for inputting aquaculture tail water into the fluidized bed; the flow value obtained by real-time reading by the flow sensor is recorded as the water inlet flow.

[0010] The flow sensor is placed in a straight pipe position more than 10 times the pipe diameter away from the flow valve to avoid the turbulence when the water just enters the pipe to ensure the accuracy of the measurement. If an electromagnetic flowmeter is used, it is necessary to regularly remove the dirt or biofilm on the electrode to prevent the loss of accuracy. The inlet flow measurement belongs to the input rate of the tail water to be treated into the fluidized bed, so the excessive inlet flow and aeration volume can easily lead to the breakage of fluidized medium particles.

[0011] Further, in step S200, the method for obtaining the aeration rate from the aeration device of the fluidized bed in real time is: the fluidized bed is connected to a flow meter installed in the aeration device through a PLC controller or a SCADA monitor, and the aeration rate is measured and obtained from the flow meter in real time; wherein the flow meter is any one of a thermal gas flow meter, a differential pressure flow meter or a rotor flow meter; and the flow meter is arranged in the main gas source pipeline of the aeration device;

[0012] Further, in step S300, when the change rate of the water inlet flow exceeds the threshold, the method for performing adaptive aeration rate adjustment intervention is: preset a numerical variable as the change rate threshold VRY_TH, and its value range is VRY_TH∈[0.5%,10%]; preset a time length as the monitoring interval MNT_ITV, and its value range is MNT_ITV∈[20,100] seconds; record the water inlet flow once every monitoring interval, if the ratio of the water inlet flow at one moment to the previous moment is greater than 1+VRY_TH, or less than 1-VRY_TH, it is considered that the change rate of the water inlet flow exceeds the threshold, and adaptive aeration rate adjustment intervention is performed.

[0013] It should be noted that the change of water flow is usually related to the breeding ecology of the farm. Therefore, its change cycle is related to the species, season and breeding water replacement strategy in the breeding ecology, and often presents irregular water volume changes. Existing fluidized bed equipment usually does not directly adjust the aeration rate dynamically according to the water inlet, because the aeration rate control factors also include the degree of water pollution and water temperature, and does not consider the impact of aeration rate changes on fluidized medium particles, and considers the risk of damage to particle integrity. When the matching degree between water inlet and aeration rate is insufficient, the first triggering condition is often that the rate of change of water flow exceeds the tolerance range. Conventional and existing aeration control usually cannot adapt to and feedback this matching degree in time.

[0014] Further, in step S301, the method of constructing an aeration adaptation model through the water inlet flow rate and the aeration rate to obtain the adaptation pairing amount is: record the array formed by the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[1.5,3] hours; within the detection period, record the time scale of obtaining the water vapor control array as a recording point; all the recording points correspond to the water vapor control array to form a water vapor control sequence;

[0015] The Bootstrap method is used to resample the water vapor regulation sequence and generate PQt sample sequences. The constraint condition for generating the sample sequence is that the number of recording points in the sample sequence is the same as the number of recording points in the detection period; PQt is a preset integer, PQt∈[500,1000], and each Bootstrap sample can be regarded as a re-collected virtual experimental data, reflecting the uncertainty between samples.

[0016] The total number of times the water vapor control array corresponding to each recording point appears in all samples is recorded as ffQt, and ffQt is arranged from large to small, and the recording points corresponding to the elements in the top 50% are selected as fluctuation singular points; since all elements in the samples constructed by the Bootstrap method are derived from the original data set, the water vapor control array corresponding to each recording point is repeatedly used to construct the sample, so it is reasonable to count the total number of occurrences.

[0017] The average value of all water vapor regulation arrays in each sample is recorded as the adaptation measurement group, and the sum of the Manhattan distances between the water vapor regulation array of any recording point and each adaptation measurement group is calculated and recorded as the adaptation estimate; that is, each recording point obtains the corresponding adaptation estimate.

[0018] The principle of obtaining the adaptation estimate here is actually to calculate the difference between the recording point and different sample sequences through Manhattan distance, and then measure the relative difference between the recording points. When the adaptation estimate is larger, it means that the water flow or air flow is too strong, which is easy to break the structure of the fluidized medium particles. On the contrary, if the adaptation estimate is smaller, it means that the performance between the recording point and multiple samples is relatively consistent and can maintain the suspended state of particles in the fluidized bed. Therefore, the adaptation estimate directly reflects the fluctuation of the dynamic state of the aeration device driving the suspension of fluidized medium particles to form a fluid-like state, which is one of the risk manifestations of the collapse of the fluidized bed tailwater treatment system.

[0019] The adaptation estimation values ​​of each fluctuation singular point are set and recorded as lst{Cebb}; the water vapor control array corresponding to any recording point is reduced in dimension using the principal component analysis method, and the reduced-dimensional data obtained is recorded as the paired projection value Stpoz of the recording point;

[0020] According to the adaptation estimation value and the paired projection value, an aeration adaptation model is constructed to obtain the adaptation pairing value Nrutt:

[0021] ;

[0022] Among them, k1 is the serial number of the recording point in the detection period Gloe, Stpoz k1 is the paired projection value of the k1th record point, LCebb k1 and FCebb k1 are the cosine similarities between the water vapor control arrays of the k1th recording point and its previous and next fluctuation singular points, respectively; the ￣ symbol is the average value symbol, which is used to calculate the average value of each element in the symbol coverage formula, where each recording point represented by k1 is used as an element in the coverage formula; exp() is an exponential function with the natural constant e as the base, var() is a function for calculating variance, and log2() is a logarithmic function with 2 as the base.

[0023] Since the calculation of the adaptive pairing quantity requires the adaptive estimation value corresponding to the fluctuation singular point to be processed and obtained, the risk of the aeration device driving the fluidized medium particles to suspend and form a fluid-like dynamic state can be effectively quantified, and the probability of collapse of the fluidized bed tailwater treatment system can be reduced. However, the acquisition of the fluctuation singular point is too dependent on the influent flow rate and the aeration rate, which makes the sensitivity of the samples generated by the Bootstrap method to the original data deviate, which will greatly increase the variability between samples and cause decision-making deviations, especially in the period of dense fluctuation singular points. The problem is more prominent. However, the existing technology cannot effectively compensate for this sensitivity deviation phenomenon. In order to eliminate this influence, the present invention proposes a more preferred solution as follows:

[0024] Preferably, in step S301, the method for constructing an aeration adaptation model by using the water inlet flow rate and the aeration rate to obtain the adaptation pairing amount is as follows: record the array formed by the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[2,5] hours; within the detection period, record the time scale of obtaining the water vapor control array as the recording point; record the average value of the water vapor control array of all recording points as the control center array; obtain the Euclidean distance between the water vapor control array of any recording point and the control center array and record it as the first pairing distance Fanva; normalize the first pairing distance of each recording point to obtain the second pairing distance Sanva;

[0025] The principle of obtaining the second pairing distance here is actually based on the value obtained after normalizing the first pairing distance of each recording point. The normalization process maps the first pairing distance to a standardized range, and at the same time amplifies the value that is biased towards the maximum value, thereby increasing the weighting of the data that is biased towards the maximum value of the first pairing distance and reducing the weight of the smaller value. The second pairing distance reflects the relative deviation between the water and gas control array and the control center array of each recording point. A larger second pairing distance indicates that the recording point has a more violent fluctuation behavior, and there are signs of instability in the fluidized bed tailwater treatment system. A smaller second pairing distance indicates that the performance of the recording point is relatively stable and the aeration control is more appropriate. This processing method provides a more reliable basis for subsequent classification and judgment.

[0026] If the second pairing distance of any record point is greater than the lower quartile of all second pairing distances, the record point is recorded as an aeration adaptation position; the second pairing distances of each aeration adaptation position are constructed into a sequence Kj_LS, and if the absolute value of the difference between an element in Kj_LS and any element before it is less than the absolute value of the difference between the element and any element after it, the aeration adaptation position corresponding to the element is defined as the forward adaptation position;

[0027] For any forward adaptation position, search for the first other forward adaptation position in the forward and reverse time directions respectively, record the record points in the forward and reverse time directions as Qkj and Hkj respectively, and define the ratio of Qkj to Hkj as the cross-pairing rate KjRio; construct an aeration adaptation model based on the first pairing distance, the second pairing distance and the aeration adaptation position to obtain the adaptation pairing amount Nrutt:

[0028] ;

[0029] Where j2 is the cumulative variable, kjn is the number of aeration adaptation positions, Sanva p and KjRio p are the second pairing distance of the current record point and the cross-pairing rate with the current record point, Fanva j2 is the first pairing distance of the j2th aeration adaptation position, Fanva_G is the average of the first pairing distances of all aeration adaptation positions in the detection period Gloe, lg() is a logarithmic function with base 10, and e is a natural constant.

[0030] The current record point refers to the record point corresponding to the current moment. When a record point does not belong to the forward adaptation position, the first forward adaptation position is searched in the reverse time direction and its cross-matching rate is inherited;

[0031] Beneficial effects: Since the adaptation matching amount is calculated based on the historical data of inlet flow rate and aeration rate, it can effectively quantify the risk of fluidized medium particles collapse caused by insufficient matching between the inlet flow rate change and the aeration rate when the fluidized medium particles constructed with rice straw-modified biochar are used for aquaculture effluent treatment, thereby providing a mathematical basis for stress regulation intervention that triggers aeration demand, and ultimately preventing the fluidized medium particles constructed with rice straw-modified biochar from being crushed due to excessive aeration or a surge in water flow.

[0032] Further, in step S302, the method for controlling the aeration rate according to the adaptation pairing amount is: presetting a time period as a trend window KCT, KCT∈[5,20] minutes; defining the average value of each adaptation pairing amount within KCT minutes at the current moment as the trend pairing amount; defining the difference between the adaptation pairing amount at any moment and its previous moment as the pairing difference, constructing the pairing difference within the current hour as a pairing difference set, and recording the upper quartile and lower quartile of the pairing difference set as TRO and TRL respectively;

[0033] If the pairing difference at the current moment is greater than TRO and greater than 0, and the adaptive pairing amount at the current moment is greater than the trend pairing amount, it is considered that the aeration rate is lower than the aeration demand caused by the change in water inlet, and the aeration rate is increased by 0.1%-10%; if the pairing difference at the current moment is less than TRL and less than 0, it is considered that the aeration rate is higher than the aeration demand caused by the change in water inlet, and the aeration rate is reduced by 0.1%-10%.

[0034] Preferably, all undefined variables in the present invention, if not clearly defined, can be manually set thresholds.

[0035] The present invention also provides a rice straw modified biochar aquaculture tailwater treatment system, the rice straw modified biochar aquaculture tailwater treatment system comprising: a processor, a memory and a computer program stored in the memory and executable on the processor, the processor implementing the steps in the rice straw modified biochar aquaculture tailwater treatment method when executing the computer program, the rice straw modified biochar aquaculture tailwater treatment system can be run in computing devices such as desktop computers, notebook computers, PDAs and cloud data centers, and the executable system may include, but is not limited to, a processor, a memory, and a server cluster, and the processor executes the computer program to run in the following system units:

[0036] A flow data measurement unit is used to arrange a flow sensor at the water inlet of the fluidized bed to read the water inlet flow;

[0037] An aeration rate reading unit, used to obtain the aeration rate from the aeration device of the fluidized bed in real time;

[0038] A change rate identification unit, used to perform adaptive aeration rate adjustment intervention when the change rate of the water inlet flow exceeds a threshold;

[0039] An aeration adaptation model building unit is used to build an aeration adaptation model through water inflow and aeration rate to obtain an adaptation pairing amount;

[0040] Intervention control unit for controlling the aeration rate according to the amount of adaptation pairing.

[0041] The beneficial effects of the present invention are as follows: the present invention provides a method and system for treating aquaculture tailwater using rice straw modified biochar. Since the adaptation matching amount is calculated based on the historical data of the inlet flow rate and the aeration rate, it can effectively quantify the risk of fluidized medium particle collapse caused by insufficient matching between the inlet flow rate change and the aeration rate when the fluidized medium particles constructed by the rice straw modified biochar are used for aquaculture tailwater treatment, thereby triggering stress regulation intervention of the aeration demand, preventing the fluidized medium particles constructed by the rice straw modified biochar from being crushed due to excessive aeration or a surge in water flow, thereby avoiding problems such as pipeline blockage, reduced tailwater treatment efficiency and loss of fluidized medium particles during fluidized bed operation, improving the operation quality and service life of the fluidized bed, and greatly reducing the resource consumption and tailwater treatment efficiency of aquaculture tailwater treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The above and other features of the present invention will become more obvious by describing in detail the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings of the present invention represent the same or similar elements. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work. In the accompanying drawings:

[0043] Figure 1 Shown is a flow chart of a method for treating aquaculture tailwater using rice straw modified biochar;

[0044] Figure 2 Shown is a structural diagram of an aquaculture effluent treatment system using rice straw-modified biochar. DETAILED DESCRIPTION

[0045] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0046] like Figure 1 The figure shows a flow chart of a method for treating aquaculture tailwater using rice straw modified biochar. Figure 1 A method for treating aquaculture tailwater using rice straw modified biochar according to an embodiment of the present invention is described below. The method comprises the following steps:

[0047] S100, arranging a flow sensor at the water inlet of the fluidized bed to read the water inlet flow;

[0048] S200, obtaining the aeration rate from the aeration device of the fluidized bed in real time;

[0049] S300, when the rate of change of the water inlet flow exceeds a threshold, an adaptive aeration rate adjustment intervention is performed;

[0050] The process of adaptive aeration rate regulation intervention includes: S301, constructing an aeration adaptation model through water inlet flow and aeration rate to obtain an adaptation pairing amount; S302, controlling the aeration rate according to the adaptation pairing amount.

[0051] Further, in step S100, a flow sensor is arranged at the water inlet of the fluidized bed, and the method for reading the water inlet flow is: the flow sensor selects any one of an electromagnetic flowmeter, an ultrasonic flowmeter or an ultrasonic flowmeter, and the flow sensor is arranged in a straight pipe position more than 10 times the pipe diameter away from the flow valve in the pipeline for inputting aquaculture tail water into the fluidized bed; the flow value obtained by real-time reading by the flow sensor is recorded as the water inlet flow.

[0052] Further, in step S200, the method for obtaining the aeration rate from the aeration device of the fluidized bed in real time is: the fluidized bed is connected to a flow meter installed in the aeration device through a PLC controller or a SCADA monitor, and the aeration rate is measured and obtained from the flow meter in real time; wherein the flow meter is any one of a thermal gas flow meter, a differential pressure flow meter or a rotor flow meter; and the flow meter is arranged in the main gas source pipeline of the aeration device;

[0053] Further, in step S300, when the change rate of the water inlet flow exceeds the threshold, the method for performing adaptive aeration rate adjustment intervention is: preset a numerical variable as the change rate threshold VRY_TH, and its value range is VRY_TH∈[0.5%,10%]; preset a time length as the monitoring interval MNT_ITV, and its value range is MNT_ITV∈[20,100] seconds; record the water inlet flow once every monitoring interval, if the ratio of the water inlet flow at one moment to the previous moment is greater than 1+VRY_TH, or less than 1-VRY_TH, it is considered that the change rate of the water inlet flow exceeds the threshold, and adaptive aeration rate adjustment intervention is performed.

[0054] Further, in step S301, the method of constructing an aeration adaptation model through the water inlet flow rate and the aeration rate to obtain the adaptation pairing amount is: record the array formed by the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[1.5,3] hours; within the detection period, record the time scale of obtaining the water vapor control array as a recording point; all the recording points correspond to the water vapor control array to form a water vapor control sequence;

[0055] The Bootstrap method is used to resample the water vapor regulation sequence and generate PQt sample sequences. The constraint condition for generating the sample sequence is that the number of recording points in the sample sequence is the same as the number of recording points in the detection period; PQt is a preset integer, PQt∈[500,1000], and each Bootstrap sample can be regarded as a re-collected virtual experimental data, reflecting the uncertainty between samples.

[0056] The total number of times the water vapor control array corresponding to each recording point appears in all samples is recorded as ffQt, and ffQt is arranged from large to small, and the recording points corresponding to the elements in the top 50% are selected as fluctuation singular points; since all elements in the samples constructed by the Bootstrap method are derived from the original data set, the water vapor control array corresponding to each recording point is repeatedly used to construct the sample, so it is reasonable to count the total number of occurrences.

[0057] The average value of all water vapor regulation arrays in each sample is recorded as the adaptation measurement group, and the sum of the Manhattan distances between the water vapor regulation array of any recording point and each adaptation measurement group is calculated and recorded as the adaptation estimate; that is, each recording point obtains the corresponding adaptation estimate.

[0058] The adaptation estimation values ​​of each fluctuation singular point are set and recorded as lst{Cebb}; the water vapor control array corresponding to any recording point is reduced in dimension using the principal component analysis method, and the reduced-dimensional data obtained is recorded as the paired projection value Stpoz of the recording point;

[0059] According to the adaptation estimation value and the paired projection value, an aeration adaptation model is constructed to obtain the adaptation pairing value Nrutt:

[0060] ;

[0061] Among them, k1 is the serial number of the recording point in the detection period Gloe, Stpoz k1 is the paired projection value of the k1th record point, LCebb k1 and FCebb k1 are the cosine similarities between the water vapor control arrays of the k1th recording point and its previous and next fluctuation singular points, respectively; the ￣ symbol is the average value symbol, which is used to calculate the average value of each element in the symbol coverage formula, where each recording point represented by k1 is used as an element in the coverage formula; exp() is an exponential function with the natural constant e as the base, var() is a function for calculating variance, and log2() is a logarithmic function with 2 as the base.

[0062] Preferably, in step S301, the method for constructing an aeration adaptation model by using the water inlet flow rate and the aeration rate to obtain the adaptation pairing amount is as follows: record the array formed by the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[2,5] hours; within the detection period, record the time scale of obtaining the water vapor control array as the recording point; record the average value of the water vapor control array of all recording points as the control center array; obtain the Euclidean distance between the water vapor control array of any recording point and the control center array and record it as the first pairing distance Fanva; normalize the first pairing distance of each recording point to obtain the second pairing distance Sanva;

[0063] If the second pairing distance of any record point is greater than the lower quartile of all second pairing distances, the record point is recorded as an aeration adaptation position; the second pairing distances of each aeration adaptation position are constructed into a sequence Kj_LS, and if the absolute value of the difference between an element in Kj_LS and any element before it is less than the absolute value of the difference between the element and any element after it, the aeration adaptation position corresponding to the element is defined as the forward adaptation position;

[0064] For any forward adaptation position, search for the first other forward adaptation position in the forward and reverse time directions respectively, record the record points in the forward and reverse time directions as Qkj and Hkj respectively, and define the ratio of Qkj to Hkj as the cross-pairing rate KjRio; construct an aeration adaptation model based on the first pairing distance, the second pairing distance and the aeration adaptation position to obtain the adaptation pairing amount Nrutt:

[0065] ;

[0066] Where j2 is the cumulative variable, kjn is the number of aeration adaptation positions, Sanva p and KjRio p are the second pairing distance of the current record point and the cross-pairing rate with the current record point, Fanva j2 is the first pairing distance of the j2th aeration adaptation position, Fanva_G is the average of the first pairing distances of all aeration adaptation positions in the detection period Gloe, lg() is a logarithmic function with base 10, and e is a natural constant.

[0067] Further, in step S302, the method for controlling the aeration rate according to the adaptation pairing amount is: presetting a time period as a trend window KCT, KCT∈[5,20] minutes; defining the average value of each adaptation pairing amount within KCT minutes at the current moment as the trend pairing amount; defining the difference between the adaptation pairing amount at any moment and its previous moment as the pairing difference, constructing the pairing difference within the current hour as a pairing difference set, and recording the upper quartile and lower quartile of the pairing difference set as TRO and TRL respectively;

[0068] If the pairing difference at the current moment is greater than TRO and greater than 0, and the adaptive pairing amount at the current moment is greater than the trend pairing amount, it is considered that the aeration rate is lower than the aeration demand caused by the change in water inlet, and the aeration rate is increased by 0.1%-10%; if the pairing difference at the current moment is less than TRL and less than 0, it is considered that the aeration rate is higher than the aeration demand caused by the change in water inlet, and the aeration rate is reduced by 0.1%-10%.

[0069] The embodiment of the present invention provides a rice straw modified biochar aquaculture tailwater treatment system, such as Figure 2 Shown is a structural diagram of an aquaculture effluent treatment system of a rice straw-modified biochar according to the present invention. The aquaculture effluent treatment system of a rice straw-modified biochar according to this embodiment comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned embodiment of the aquaculture effluent treatment method of a rice straw-modified biochar are implemented.

[0070] The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to run in the following units of the system:

[0071] A flow data measurement unit is used to arrange a flow sensor at the water inlet of the fluidized bed to read the water inlet flow;

[0072] An aeration rate reading unit, used to obtain the aeration rate from the aeration device of the fluidized bed in real time;

[0073] A change rate identification unit, used to perform adaptive aeration rate adjustment intervention when the change rate of the water inlet flow exceeds a threshold;

[0074] An aeration adaptation model building unit is used to build an aeration adaptation model through water inflow and aeration rate to obtain an adaptation pairing amount;

[0075] Intervention control unit for controlling the aeration rate according to the amount of adaptation pairing.

[0076] The aquaculture tailwater treatment system of rice straw modified biochar can be run in computing devices such as desktop computers, laptops, PDAs and cloud servers. The aquaculture tailwater treatment system of rice straw modified biochar can include, but is not limited to, processors and memories. Those skilled in the art can understand that the example is only an example of an aquaculture tailwater treatment system of rice straw modified biochar, and does not constitute a limitation on an aquaculture tailwater treatment system of rice straw modified biochar. It can include more or fewer components than the example, or a combination of certain components, or different components. For example, the aquaculture tailwater treatment system of rice straw modified biochar can also include input and output devices, network access devices, buses, etc.

[0077] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the operation system of the aquaculture tailwater treatment system of rice straw modified biochar, and uses various interfaces and lines to connect the various parts of the entire aquaculture tailwater treatment system of rice straw modified biochar.

[0078] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the aquaculture tailwater treatment system of rice straw modified biochar by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0079] Although the description of the present invention has been quite detailed and has been described in particular with respect to several described embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, so as to effectively cover the intended scope of the present invention. In addition, the present invention is described above with the embodiments foreseeable by the inventors, and its purpose is to provide a useful description, and those non-substantial changes to the present invention that are not currently foreseen may still represent equivalent changes of the present invention.

Claims

1. A method for treating aquaculture tailwater using rice straw modified biochar, characterized in that: The method comprises the following steps: S100, arranging a flow sensor at the water inlet of the fluidized bed to read the water inlet flow; S200, obtaining the aeration rate from the aeration device of the fluidized bed in real time; S300, when the rate of change of the water inlet flow exceeds a threshold, an adaptive aeration rate adjustment intervention is performed; The process of adaptive aeration rate regulation intervention includes: S301, constructing an aeration adaptation model through water inflow and aeration rate to obtain an adaptation pairing amount; S302, controlling the aeration rate according to the adaptation pairing amount; The method for obtaining the adaptive pairing amount in step S301 is to record the array composed of the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[1.5,3] hours; within the detection period, record the time scale of obtaining the water vapor control array as a recording point; all the recording points correspond to the water vapor control array to form a water vapor control sequence; The Bootstrap method is used to resample the water vapor regulation sequence and generate PQt sample sequences. The constraint condition for generating the sample sequence is that the number of recording points in the sample sequence is the same as the number of recording points in the detection period; the total number of times the water vapor regulation array corresponding to each recording point appears in all samples is recorded as ffQt, and ffQt is arranged from large to small and the recording points corresponding to the elements in the first 50% are selected as fluctuation singular points; The average value of all water vapor control arrays in each sample is recorded as the adaptation measurement group. The sum of the Manhattan distances between the water vapor control array of any recording point and each adaptation measurement group is calculated and recorded as the adaptation estimation value. The adaptation estimation values ​​of each fluctuation singular point are formed into a set and recorded as lst{Cebb}. The water vapor control array corresponding to any recording point is reduced in dimension using the principal component analysis method, and the reduced-dimension data is recorded as the paired projection value Stpoz of the recording point. The aeration adaptation model is constructed based on the adaptation estimation value and the paired projection value to obtain the adaptation pairing value Nrutt: ； Among them, k1 is the serial number of the recording point in the detection period Gloe, Stpoz k1 is the paired projection value of the k1th record point, LCebb k1 and FCebb k1 are the cosine similarities between the water vapor control arrays of the k1th recording point and its previous and next fluctuation singular points; Alternatively, the method for obtaining the adaptation pairing amount in step S301 is: record the array composed of the water inlet flow rate and the aeration rate as the water vapor control array; set a time period as the detection period Gloe, Gloe∈[2,5] hours; within the detection period, record the time scale of obtaining the water vapor control array as the recording point; record the average value of the water vapor control array of all recording points as the control center array; obtain the Euclidean distance between the water vapor control array of any recording point and the control center array and record it as the first pairing distance Fanva; normalize the first pairing distance of each recording point to obtain the second pairing distance Sanva; If the second pairing distance of any record point is greater than the lower quartile of all second pairing distances, the record point is recorded as an aeration adaptation position; the second pairing distances of each aeration adaptation position are constructed into a sequence Kj_LS, and if the absolute value of the difference between an element in Kj_LS and any element before it is less than the absolute value of the difference between the element and any element after it, the aeration adaptation position corresponding to the element is defined as the forward adaptation position; For any forward adaptation position, search for the first other forward adaptation position in the forward and reverse time directions respectively, record the recorded points in the forward and reverse time directions as Qkj and Hkj respectively, and define the ratio of Qkj to Hkj as the cross-pairing rate KjRio; construct an aeration adaptation model based on the first pairing distance, the second pairing distance and the aeration adaptation position to obtain the adaptation pairing amount: ; Where j2 is the cumulative variable, kjn is the number of aeration adaptation positions, Sanva p and KjRio p are the second pairing distance of the current record point and the cross-pairing rate with the current record point, Fanva j2 is the first pairing distance of the j2th aeration adaptation position, Fanva_G is the average of the first pairing distances of all aeration adaptation positions in the detection period Gloe, lg() is a logarithmic function with base 10, and e is a natural constant.

2. The method for treating aquaculture tailwater using rice straw modified biochar according to claim 1, characterized in that: In step S100, a flow sensor is arranged at the water inlet of the fluidized bed, and the method for reading the water inlet flow is: the flow sensor selects any one of the electromagnetic flowmeter, ultrasonic flowmeter or sonic flowmeter, and the flow sensor is arranged in a straight pipe position more than 10 times the pipe diameter away from the flow valve in the pipeline for inputting aquaculture tail water from the fluidized bed; the flow value obtained by real-time reading by the flow sensor is recorded as the water inlet flow.

3. The method for treating aquaculture tailwater using rice straw modified biochar according to claim 1, characterized in that: In step S200, the method for obtaining the aeration rate from the aeration device of the fluidized bed in real time is: the fluidized bed is connected to the flow meter installed in the aeration device through a PLC controller or a SCADA monitor, and the aeration rate is measured and obtained from the flow meter in real time; wherein the flow meter is any one of a thermal gas flow meter, a differential pressure flow meter or a rotor flow meter; and the flow meter is arranged in the main gas source pipeline of the aeration device.

4. The method for treating aquaculture tailwater using rice straw modified biochar according to claim 1, characterized in that: In step S300, when the rate of change of the water inlet flow exceeds the threshold, the method for performing adaptive aeration rate adjustment intervention is: preset a numerical variable as the rate of change threshold VRY_TH, and its value range is VRY_TH∈[0.5%,10%]; preset a time length as the monitoring interval MNT_ITV, and its value range is MNT_ITV∈[20,100] seconds; record the water inlet flow once every monitoring interval, if the ratio of the water inlet flow at one moment to the previous moment is greater than 1+VRY_TH, or less than 1-VRY_TH, it is considered that the rate of change of the water inlet flow exceeds the threshold, and adaptive aeration rate adjustment intervention is performed.

5. The method for treating aquaculture tailwater using rice straw modified biochar according to claim 1, characterized in that: In step S302, the method for controlling the aeration rate according to the adaptation pairing amount is: presetting a time period as a trend window KCT, KCT∈[5,20] minutes; defining the average value of each adaptation pairing amount within KCT minutes at the current moment as the trend pairing amount; defining the difference between the adaptation pairing amount at any moment and its previous moment as the pairing difference, constructing the pairing difference within the current hour as a pairing difference set, and recording the upper quartile and lower quartile of the pairing difference set as TRO and TRL respectively; If the current pairing difference is greater than TRO and greater than 0, and the current adaptation pairing amount is greater than the trend pairing amount, increase the aeration rate by 0.1%-10%; if the current pairing difference is less than TRL and less than 0, reduce the aeration rate by 0.1%-10%.

6. A rice straw modified biochar aquaculture tailwater treatment system, characterized in that: The aquaculture tailwater treatment system of rice straw modified biochar comprises: a processor, a memory and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the aquaculture tailwater treatment method of rice straw modified biochar described in any one of claims 1 to 5 are implemented. The aquaculture tailwater treatment system of rice straw modified biochar runs on a desktop computer, a laptop computer, a PDA and a computing device in a cloud data center.

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